• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.27 no.2
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• pp.146-159
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• 2023

This paper proposes a hybrid algorithm combining K-means clustering and watershed algorithms for flower segmentation and counting. We use the K-means clustering algorithm to obtain the main colors in a complex background according to the cluster centers and then take a color space transformation to extract pixel values for the hue, saturation, and value of flower color. Next, we apply the threshold segmentation technique to segment flowers precisely and obtain the binary image of flowers. Based on this, we take the Euclidean distance transformation to obtain the distance map and apply it to find the local maxima of the connected components. Afterward, the proposed algorithm adaptively determines a minimum distance between each peak and apply it to label connected components using the watershed segmentation with eight-connectivity. On a dataset of 30 images, the test results reveal that the proposed method is more efficient and precise for the counting of overlapped flowers ignoring the degree of overlap, number of overlap, and relatively irregular shape.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.357-362
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• 2019

This paper proposes a model and train method that can real-time detect objects and distances estimation based on a monocular camera by applying deep learning. It used YOLOv2 model which is applied to autonomous or robot due to the fast image processing speed. We have changed and learned the loss function so that the YOLOv2 model can detect objects and distances at the same time. The YOLOv2 loss function added a term for learning bounding box values x, y, w, h, and distance values z as 클래스ification losses. In addition, the learning was carried out by multiplying the distance term with parameters for the balance of learning. we trained the model location, recognition by camera and distance data measured by lidar so that we enable the model to estimate distance and objects from a monocular camera, even when the vehicle is going up or down hill. To evaluate the performance of object detection and distance estimation, MAP (Mean Average Precision) and Adjust R square were used and performance was compared with previous research papers. In addition, we compared the original YOLOv2 model FPS (Frame Per Second) for speed measurement with FPS of our model.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.14-22
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• 2014

An autonomous vehicle requires a technology of generating maps by recognizing surrounding environment. The recognition of the vehicle's environment can be achieved by using distance information from a 2D laser scanner and color information from a camera. Such sensor information is used to generate 2D or 3D maps. A 2D map is used mostly for generating routs, because it contains information only about a section. In contrast, a 3D map involves height values also, and therefore can be used not only for generating routs but also for finding out vehicle accessible space. Nevertheless, an autonomous vehicle using 3D maps has difficulty in recognizing environment in real time. Accordingly, this paper proposes the technology for generating 2D maps that guarantee real-time recognition. The proposed technology uses only the color information obtained by removing height values from 3D maps generated based on the fusion of 2D laser scanner and camera data.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.300-312
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• 2009

An indoor location-based service cannot be realized unless the indoor positioning problem is solved. However, the cost-effective indoor positioning systems are suffering from their inaccurateness. This paper proposes a map information-based correction method for the indoor positioning systems. Using our Kalman filter with map information-based appropriate parameter values, our method estimates the track of the moving object, then it performs the Frechet Distance-based map matching on the obtained track. After that it applies our real time correction method. In order to verify efficiency of our method, we also provide our test results.

• Journal of Korea Multimedia Society
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• v.13 no.4
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• pp.582-593
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• 2010

Recently the commercial value of GIS(geographic information system) has been increased with growing application demands of spatial information in life space. Also, GIS has been expanded to the integrated information system that provides the ease access to map information by public users and also the combined service of GIS map data and various multimedia contents. But several security problems of GIS map data have brought up at GIS industries, such as the illegal copy and distribution of GIS map data. Furthermore, the copyright protection of GIS map data has not been researched yet compared with image and video contents. This paper presents a polyline based watermarking scheme for the copyright protection of GIS vector map. The proposed scheme analyzes the structure of vector map and embeds adaptively the watermark by using the distance distribution of polyline components. From experimental results, we verified that the proposed scheme satisfies the invisibility and the robustness of geometrical attacks.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.300-302
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• 2008

For the evaluation of wind resources, numerical simulation was carried out as a tool for establishing wind map around the korean peninsula. Initial and boundary condition are given by 3 hourly RDAPS(Regional Data Assimilation and Prediction System) data of KMA(Korea Meteorology Administration) and high resolution terrain elevation land cover(30 seconds) data from USGS(United States Geological Survey). Furthermore, Data assimilation was adopted to improve initial meteorological data with buoy and QuikSCAT seawinds data. The simulation was performed from 2003 to 2006 year. To understand wind data correctly in complex terrain as the korean peninsula, at this research, Wind map was classified 4 categories by distance from coastline and elevation.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.8
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• pp.62-71
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• 2009

In mobile robotics, ultrasonic sensors became one of the most popular devices for collision avoidance and navigation primarily due to data robustness, the easy availability of low-cost systems, their compact size, simple circuits, and their ease in interfacing with computers. However, ultrasonic sonic sensors are subject to noise which results in inaccuracy of mapping and localization of the robot. This paper introduces a new approach to enhance environmental maps based on ultrasonic range data using linear interpolation and Newton interpolation. The simulation and experimental results show that the proposed method improves of the accuracy of the map through better distance estimation between the mobile robot and obstacles.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.4
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• pp.37-50
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• 2007

Dramatic development of information technology requires new type of sales strategy to enterprise S/W dealers. That is, one should thoroughly consider diversified types of enterprise S/W and more elaborated consumer needs to establish successful sales strategy. However, various factors that should be considered in establishing enterprise S/W sales strategy are different according to types of enterprise S/W and hard to be managed systematically which led to the current situation where they have not been discussed enough. Therefore, this study introduced the relationship between the factors that affect selection of enterprise S/W using the concept of cognitive map on various enterprise S/W sales cases. Through this process, this study grouped the cognitive maps of similar cases to introduce their characteristics and made this result to be practically useful to enterprise S/W sales strategy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.241-243
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• 2010

Previous approaches to the 2D to 3D conversion problem require heavy computation or considerable amount of user input. In this paper, we propose a rather simple method in estimating the depth map from a single image using a monocular depth cue: haze. Using the haze imaging model, we obtain the distance information and estimate a reliable depth map from a single scenery image. Using the depth map, we also suggest an algorithm that converts the single image to 3D stereoscopic images. We determine a disparity value for each pixel from the original 'left' image and generate a corresponding 'right' image. Results show that the algorithm gives well refined depth maps despite the simplicity of the approach.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.76-81
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• 1993

This paper presents an Auto-Drive-Guidance System which provides a path to the destination with the shortest driving distance(or time), as well as service information such as the location of gas stations, hospitals, or police stations. This system displays on the monitor screen the best driving path to the destination, points the current car position on the map, informs the driver of current position by voice whenever the car passes well-known places, or displays the map the driver wishes to view. With this system, driving becomes more comfortable, and traffic jams will be greatly reduced. As a result, gasoline consumption will be reduced and so air pollution. The system can also be applied to such areas as communication network, geographic map, and tour information.